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TradingAgents/CLAUDE.md

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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

TradingAgents is a Python-based multi-agent LLM financial trading framework that simulates a trading firm with specialized AI agents. It uses LangGraph for agent orchestration and supports multiple LLM providers.

Key Architecture

The system implements a collaborative multi-agent architecture:

  • Analysts: Analyze company fundamentals, market trends, sentiment, and news
  • Researchers: Bull and Bear researchers debate investment opportunities
  • Risk Managers: Evaluate and debate risk levels
  • Research Manager: Synthesizes research into actionable decisions
  • Trader: Executes decisions based on collective intelligence

Agent communication flows through LangGraph workflows defined in tradingagents/graph/.

Common Development Commands

# Install dependencies
pip install -r requirements.txt

# Install package in development mode
pip install -e .

# Run the CLI application
python -m cli.main
# or after installation:
tradingagents

# Start the API server
python -m tradingagents_api.start_server

# Run the main example script
python main.py

Important Configuration

  1. API Keys: Set in environment variables or .env file:

    • OPENAI_API_KEY
    • ANTHROPIC_API_KEY
    • FINNHUB_API_KEY
    • OPENROUTER_API_KEY
    • LANGCHAIN_API_KEY (for tracing)

  2. LLM Configuration: Modify tradingagents/default_config.py:

    • Default model: "openai/gpt-4o-mini"
    • Supports OpenAI, Anthropic, Google, Ollama, OpenRouter
    • Temperature settings for each agent type

  3. Python Version: Requires Python >=3.10 (3.12 recommended)

Project Structure Guidelines

  • Agent implementations: tradingagents/agents/
  • Data fetching logic: tradingagents/dataflows/
  • LangGraph workflows: tradingagents/graph/
  • API endpoints: tradingagents-api/app/api/v1/endpoints/
  • CLI interface: cli/

API Development

The FastAPI application in tradingagents-api/ provides REST endpoints:

  • Market analysis: /api/v1/reports/market
  • Sentiment analysis: /api/v1/reports/sentiment
  • News analysis: /api/v1/reports/news
  • Fundamentals: /api/v1/reports/fundamentals

API uses JWT authentication with API key fallback. See tradingagents-api/README.md for deployment details.

Testing Approach

Currently no formal test suite exists. When implementing tests:

  • Use pytest for unit testing
  • Test agent logic in isolation
  • Mock external API calls (FinnHub, Yahoo Finance)
  • Test LangGraph workflow transitions

Code Conventions

  • Use type hints throughout
  • Follow async/await patterns for I/O operations
  • Implement Pydantic models for data validation
  • Keep agent logic modular and testable
  • Use environment variables for configuration
  • Log important decisions and errors

Key Dependencies

  • LangChain/LangGraph: Agent orchestration
  • yfinance/finnhub: Market data
  • backtrader: Backtesting framework
  • FastAPI: REST API
  • Chainlit: UI interface
  • Rich: CLI formatting